TH-CD-303-04: A Method for Assessing Ground-Truth Accuracy of a Motion Model Based 4DCT Technique

Abstract

Purpose: To develop a technique that validates a breathing motion model and its reconstructed phase-specific image generation process using the original free-breathing images as ground truths. Methods: 16 lung cancer patients underwent the published protocol where 25 free-breathing fast helical CT scans were acquired with a simultaneous breathing surrogate. The first image was arbitrarily selected as the reference image. For constructing patient-specific lung motion model, state-of-the-art deformable image registration was employed to determine lung tissue displacement. The motion model was used, along with the free-breathing phase information of the original 25 image datasets, to generate a set of deformation vector fields (DVF) that mapped the reference image to the 24 non-reference images. The set of original images was simulated by applying the inverted model DVF to the reference image. To test the robustness of model simulation over the entire lung region, the model simulated image was deformably registered to the original scan. The resulting deformation vector magnitude evaluated the point-wise discordance in the lung region. Results: Qualitative comparison of image overlay showed excellent agreement between the simulated and the original images. The mean error across the patient cohort was 1.15±0.37 mm, while the mean 95th percentile error was 2.47±0.78 mm. Conclusion: Despite a large variety of breathing patterns and lung deformations, the proposed technique can accurately reproduce the original free-breathing helical CT scans, suggesting its applicability to a wide range of patients. The proposed ground truth based analysis is unique in CT-based breathing motion modeling for radiation therapy and will provide uncertainty estimations in the model-based 4DCT breathing motion estimate of tumors and normal organs. This work was supported in part by NIH R01 CA096679